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Using Machine Learning to Solve Critical Challenges in Healthcare IT

Artificial Intelligence and Machine Learning are rapidly gaining momentum in Healthcare and - as some say - on the verge of becoming the most important breakthrough for healthcare since penicillin.

Most of these technological advances rightfully target improvements of patient care - for example in the areas of better diagnostic services, precision medicine, personalized drug development and decision support.

Healthcare IT is undergoing similar revolutionary transformations with AI and Machine Learning techniques that are helping to address critical challenges. Two of the following our recent use cases highlight these challenges and reflect on successful applications of AI and ML in our practices.

COMPLEX PROCESSES FOR PATIENT IDENTIFICATION

Reliable patient matching is one of the most complex and most important elements in communications between Health systems. Matching records to the correct individual is more complicated when patients receive care in multiple settings and when organizations and providers use different systems to share records electronically.

In the process of creating rare diseases registry one of the organizations we have been working with has a need to identify and capture medical records matching target disease criteria. On behalf of this client we have integrated with multiple healthcare institutions and are receiving all visit summaries from these institutions. Only small number of the visiting patients match the eligibility criteria and expected to be captured in the registry. Additionally, records coming from these external systems have to be correctly matched to patients which are already in the registry.

We have utilized and integrated existing open-source machine learning components with proprietary algorithms developed and optimized in-house.

We subsequently trained these components on large sets of synthetic and real-life patient records to achieve desired matching accuracy and included these matching processes in the existing data ingestion pipeline.    

The above infrastructure is built as part of the integration pipeline based on Intersystems HealthConnect integration engine. The machine learning components are implemented using Python libraries and a special adaptor was built into HealthConnect to support patient matching workflow. The infrastructure is deployed on Microsoft Azure under Docker environment.


About Us

First Line Software is a premier provider of custom software development, technology enablement services and value-add consulting in big data engineering, digitalization, intellectual integration, industrial Internet, and IoT, digital media and marketing, and enterprise content management as well as healthcare IT.

Headquartered in the US, First Line employs 500+ staff globally. First Line team and company culture is centered around subject matter expertise, technical excellence, consulting capabilities and proven methodologies, with a strong focus on Agile and Intellectual Integration.

The company has been recognized with multiple annual rankings and awards by the International Association of Outsourcing Professionals (IAOP), Global Services, CorporateLiveWire, Insights Success and CNews. We were the first to be awarded the Scrum Capability Medallion by Scrum, Inc. Most recently, research firm Gartner included FirstLine in their first ever Market Guide for Technology Integrators (2014) and the Cool Vendor in Applications Services 2015 Report. We are active members in Object Management Group and Industrial Internet Consortium. FLS is also an EPiServer Premium Solutions Partner.